Towards an Adaptive Gamification Recommendation Approach for Interactive Learning Environments
摘要
In this article we provide an innovative approach to effectively combine adaptive learning with a personalized recommendation to transform educational technology. With the use of an intelligent recommendation system, our adaptive gamified learning environment can instantly modify content to each learner’s unique learning needs and preferences. Based on extensive understanding of adaptive learning, gamification, and recommendation systems, the process consists of designing an all-encompassing system structure that ideally integrates adaptive content with a recommendation engine. Initial user testing findings show significant improvements in performance along with greater user engagement, confirming the effectiveness of our approach. The work promises to make an impact in the context of current education through contributing to the current interaction regarding educational technology and offering educators an effective basis to establish engaging, personalized, and dynamic learning experiences. Our recommendation model can be used by other gamified educational platforms for the adaptation of educational content and gamification according to a learner profile.